Effect of pH and ethanol on Lactiplantibacillus plantarum in red must fermentation: potential use of wine lees

Grapevine cultivation is threatened by the global warming, which combines high temperatures and reduced rainfall, impacting in wine quality and even plant survival. Breeding for varieties resilient to these challenges must address plant traits such as tolerance to supraoptimal temperatures and optimized water use efficiency while minimizing productivity and quality losses. Stomatal abundance (SA) determines the maximum leaf potential for transpiration and thus water loss and cooling. Since SA results from a developmental process during leaf emergence and growth, knowledge on the genetic control of this process would provide specific targets for modification.

Microorganism-based inoculants have been suggested as a viable solution to mitigate the adverse effects of climate change on viticulture. However, the actual effectiveness of these inoculants when applied under field conditions remains a challenge, and their effects on the existing soil microbiota are still uncertain. This study investigates the impact of arbuscular mycorrhizal fungi inoculation on grapevine performance and microbiome. The study was conducted in a vineyard of Callet cultivar in Binissalem, Mallorca, Spain. Two different treatments were applied: control and inoculation with commercial mycorrhizae complex of Rhizoglomus irregulare applied to plants through irrigation.

The nitrogen composition of the grapes directly affects the developments of alcoholic fermentation and influences the final aromatic composition of the wines. The aim of this study was to determine the effect and efficiency of foliar applications of urea on the nitrogen composition of grapes. This study was carried out during 2023 vintage and in the Chenin vineyard located in Estacion Experimental Mendoza (Argentina). Three urea concentrations 3, 6 and 9 Kg N/ha (C1, C2, and C3, respectively) and control (T) were applied in this vineyard at veraison.

The main objective of the work was to develop a simple, robust and selective analytical tool that allows predicting the authenticity of Tempranillo wines from DOCa Rioja. The techniques of voltammetry and absorbance-transmission and fluorescence excitation emission matrix (A-TEEM) spectroscopy have been applied in combination with machine learning (ML) algorithms to classify red wines from DOCa Rioja according to region (Alavesa, Alta or Oriental) and category (young, crianza or reserva).

The vital role of soils in supporting life on our planet cannot be overstated. Soils provide numerous ecosystem services and functions, including biomass production, carbon sequestration, physical support, biological habitat, and genetic reserve, among others. Understanding the characteristics and sensitivity of soils in a specific terroir, along with effective soil management practices, is crucial for the sustainable management of natural resources.